An improved joint model: POS tagging and dependency parsing

Dependency parsing is a way of syntactic parsing and a natural language that automatically analyzes the dependency structure of sentences, and the input for each sentence creates a dependency graph. Part-Of-Speech (POS) tagging is a prerequisite for dependency parsing. Generally, dependency parsers do the POS tagging task along with dependency parsing in a pipeline mode. Unfortunately, in pipeline models, a tagging error propagates, but the model is not able to apply useful syntactic information. The goal of joint models simultaneously reduce errors of POS tagging and dependency parsing tasks. In this research, we attempted to utilize the joint model on the Persian and English language using Corbit software. We optimized the model's features and improved its accuracy concurrently. Corbit software is an implementation of a transition-based approach for word segmentation, POS tagging and dependency parsing. In this research, the joint accuracy of POS tagging and dependency parsing over the test data on Persian, reached 85.59% for coarse-grained and 84.24% for fine-grained POS. Also, we attained 76.01% for coarse-grained and 74.34% for fine-grained POS on English

Designing an intelligent computer game for prediction of dyslexia based on cognitive science

Background and Objectives:The ability to read is one of the abilities effective in quality of life. From among the children with normal intelligence and more, dyslexic students have a significant lack of readability due to their age and their ability to intelligence. In any planning and designing a treatment plan for these people, diagnosis is a necessary first step. Early and timely recognition of this disorder is essential to prevent the negative consequences of impairment. Method and Materials: The tool that is used for data gathering is an intelligent computer game that designed and developed during this study. In this study, we looked for a method for predicting dyslexia that is not read-based, so that treatment with dyslexia can be initiated before they begin to teach. The purpose of this study was to develop an intelligent diagnostic system in the form of a computer game based on artificial intelligent and supervised machine learning to predict dyslexia based on the cognitive differences of dyslexic children with other children. Games can provide a less stressful or a stress-free way for the children so that the child do not even realize that it is being measured. The intelligent diagnostic system was trained with the help of thirty students. Findings: The results of the study on performance of this intelligent system showed that the provided computer game has the ability to predict dyslexia with a probability higher than 97%. Conclusion: In this study, a smart computer game is presented that has the ability to predict dyslexia in children. This system uses to predict a cognitive difference between resuscitated and dyslexic children. The high accuracy of the system in diagnosis shows that dyslexia can be predicted by relying on cognitive differences and this prediction can be done at younger ages and before providing reading instruction to children. In this case, it is possible to prevent the various negative effects of dyslexia on the child, family and society by timely intervention. This method is presented in the form of a computer game, and the advantage of games is that games can provide a way with little or no stress and interesting for the child so that the child does not even realize that he is being tested. The next advantage is the availability of games

Haplothrips zabolius sp. n., a new species from Sistan & Baluchestan province, southeast of Iran (Thysanoptera: Phlaeothripidae)

Haplothrips zabolius sp. n. is described from two plant species, Cynodon dactylon (Poaceae) and Plantago lanceolata (Plantaginaceae) from the southeast of Iran. The new species is apparently close to some grass-living Haplothrips species: H. aculeatus (Fabricius), H. eragrostidis Priesner and H. hukkineni Priesner. Most specimens of the new species have only one sense cone on the antennal segment III, but it is unusual among Iranian members of the genus in having another sense cone on the antennal segment III in a few specimens

Customer knowledge management in software development: a descriptive field survey

Customer Knowledge (CK) plays an important role in the production of high quality and innovative software products. However, there has been little comprehensive academic research on the ‘enablers’ of customer-specific knowledge. Therefore, study aims to analyze Customer Knowledge Management (CKM) ‘enablers’ for enterprise software development companies. Survey questionnaires were distributed to software companies and results showed that most firms focus their efforts more on ‘Technological Infrastructure’ and less on ‘Human’ and ‘Organizational’ CKM enablers. Results demonstrated low positive percent ratings for ‘Human Antecedents’ (Individual Competences & Skills) and ‘Organizational’ enablers (‘Customer Involvement’, CKM ‘Strategy Development’ and ‘Training’). This study contributes to the CKM domain by revealing essential elements that better enable enterprise software development firms to enhance software quality and produce innovative products. The author recommends that software companies place greater emphasis on ‘Human’ and ‘Organizational’ enablers for the successful implementation of CKM strategies

A new differential configuration suitable for realization of high CMRR, all-pass/notch filters

#yayıncısurumuyok# ; Tam metin hakemden geçmiş kopyadır.In this paper, a new configuration suitable for realization of differential input-differential output first order, second order all-pass and notch filters with high CMRR is given. The proposed configuration uses two negative type second-generation current conveyors (CCII-), and three admittances. Two first order and one second order all-pass filters and a notch filter (tunable if current controlled conveyor CCCII is used) are extracted from the proposed configuration. Tracking error, element mismatch, sensitivity analysis, simulation and experimental results are included

Histopathological evaluation of the effectiveness of glycyrrhizic acid as a radioprotector against the development of radiation-induced lung fibrosis

Background: Radiotherapy of the thorax often causes lung inflammation leading to fibrosis. Objectives: The aim of this study was to investigate whether the use of glycyrrhizic acid (GLA) could improve the development of lung fibrosis in irradiated animals. Materials and Methods: Wistar rats were divided into four groups. Group A rats received thoracic irradiation. Rats in group B received GLA and irradiation. Group C received GLA and no irradiation. Group D received no GLA and irradiation. GLA was administered at a dose of 4 mg/kg body weight using an intraperitoneal injection one hour before thoracic irradiation. Radiation therapy was delivered on a Cobalt-60 unit using a single fraction of 16 Gy. The animals were sacrificed at 32 weeks following thoracic irradiation. The lungs were dissected and blind histopathological evaluation was performed. Results: Histopathologically, a decrease (statistically not significant) in the thickening of alveolar or bronchial wall, formation of fibrous bands, and superimposed collagen were noted in the animals in group B as compared to the animals in group A. Conclusion: In this experimental study, administration of GLA one hour before thoracic irradiation may be a protective agent against radiation-induced fibrosis in animals and this model could be used in future studies. © 2016, Tehran University of Medical Sciences and Iranian Society of Radiology

Persistence of earnings and prediction of future cash flows: the role of timely recognition of bad news

Timely recognition of losses and expenses compared to revenues and increased values precipitates future expenses to match with current revenues. Thus, timely recognition of losses acts to reduce the persistence of earnings. However, it is expected that a more timely recognition of negative cash flows, as bad news, increase the power of earnings for predicting future cash flows. This study investigates the effects of the timely recognition of bad news (loss) versus the good news on the decrease of the persistence of earnings, and the effect of negative cash flows on forecasting future cash flows. In this study, two pooling type models and a panel type model have been used to estimate the persistence of earnings and cash flows. Seventy eight firms that were listed in the Tehran Stock Exchange during the period 2003–2010 were duly reviewed. The results of this research proved that the timely recognition of loss does not affect the persistence and the power of earnings for the purpose of forecasting future cash flows. The findings imply that conservatism does not distort persistence of earnings